A 23 full factorial design attempts to prevent the effect of lurking variables by

Question

Options

• Areplication
• Brandomization
• Cinteraction
• Dnone of the above
• Eall of the above

• B
  88% (21)
• C
  4% (1)
• D
  8% (2)

Explanation

Randomization of the run order is the mechanism that guards against lurking variables in a 2³ factorial design. By randomly assigning the sequence in which experimental runs are conducted, the influence of any uncontrolled variable (e.g., operator fatigue, ambient temperature drift) is spread unpredictably across all treatment combinations rather than systematically favoring some over others.

Why the distractors are wrong:

• A (Replication) increases precision and enables estimation of experimental error, but replicating a biased design just gives you more precise biased results - it does not neutralize lurking variables.
• C (Interaction) is a measurable effect between factors that factorial designs can estimate; it describes how factors influence each other, not a control mechanism against outside variables.
• D/E are therefore also wrong since B alone is correct.

Memory tip: Think "Randomize to Neutralize." Randomization doesn't eliminate lurking variables - it scrambles their effect so it can't masquerade as a treatment effect.

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